🎓 Student Performance Predictor

An AI-powered web application that predicts student academic performance based on key study habits and lifestyle factors using Machine Learning.

📊 Features

• Predicts student performance index (0-100)
• Analyzes 5 key factors:
  • Hours studied per day
  • Previous exam scores
  • Extracurricular activities participation
  • Sleep hours per day
  • Number of practice papers solved
• Provides instant predictions with personalized recommendations
• Beautiful, responsive UI with animations

🚀 Screenshot

🛠️ Tech Stack

• Backend: Flask (Python)
• Machine Learning: Scikit-learn (Linear Regression)
• Frontend: HTML5, CSS3, JavaScript
• Model: Multiple Linear Regression (R² Score: 98.88%)

📈 Model Performance

• Algorithm: Linear Regression
• R² Score: 0.9888
• Features: 5 input features
• Training Data: 10,000 student records

Feature Coefficients

Feature	Coefficient
Hours Studied	2.85
Previous Scores	1.02
Extracurricular	0.61
Sleep Hours	0.48
Papers Practiced	0.19

🏃‍♂️ Run Locally

1. Clone the repository:

git clone https://github.com/yourusername/student-performance-predictor.git
cd student-performance-predictor